Dear list, I am predicting PM measurements on a spatiotemporal grid with monthly intervals in time. At modeling time, I am looking at the experimental 3D variograms (`wireframes`) but I see that weird decreasing behavior in time (see wireframes_2008-1.eps for January 2008): there is a peak at 0 time lags, then correlation in time is much higher over different days. How can I interpret such variogram? Would it mean that there is a very high spatial variability for values on the same day, whereas temporal variability is significantly lower?
Thanks for any hint, (I can provide implementation details in case of need) Piero
wireframes_2008-1.eps
Description: PostScript document
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